5 papers
ViBE: Visual-to-M/EEG Brain Encoding via Spatio-Temporal VAE and Distribution-Aligned Projection
Ganxi Xu, Zhao-Rong Lai, Yuting Tang +6
Brain encoding models not only serve to decipher how visual stimuli are transformed into neural responses, but also represent a critical step toward visual prostheses that restore…
Deep Models, Shallow Alignment: Uncovering the Granularity Mismatch in Neural Decoding
Yang Du, Siyuan Dai, Yonghao Song +3
Neural visual decoding is a central problem in brain-computer interface research, aiming to reconstruct human visual perception and to elucidate the structure of neural representat…
UMind: A Unified Multitask Network for Zero-Shot M/EEG Visual Decoding
Chengjian Xu, Yonghao Song, Zelin Liao +3
Decoding visual information from time-resolved brain recordings, such as EEG and MEG, plays a pivotal role in real-time brain-computer interfaces. However, existing approaches prim…
AdaBrain-Bench: Benchmarking Brain Foundation Models for Brain-Computer Interface Applications
Jiamin Wu, Zichen Ren, Junyu Wang +7
Non-invasive Brain-Computer Interfaces (BCI) offer a safe and accessible means of connecting the human brain to external devices, with broad applications in home and clinical setti…
Neuro-3D: Towards 3D Visual Decoding from EEG Signals
Zhanqiang Guo, Jiamin Wu, Yonghao Song +5
Human's perception of the visual world is shaped by the stereo processing of 3D information. Understanding how the brain perceives and processes 3D visual stimuli in the real world…